A Simulation Study on Model Predictive Control and Extremum Seeking Control for Heap Bioleaching Processes

Heap bioleaching processes are of increasing interest in the mining industry to recover metals from secondary ores. Recently, it has been proposed to use feedback control to improve the rate of mineral extraction. In this paper we compare two feedback approaches, namely Model Predictive Control (MPC) and Extremum Seeking Control (ESC), to improve copper extraction in a heap bioleaching process. Simplified linear models obtained in previous work are used to design an MPC strategy incorporating input constraints. ESC is tuned to maximise copper extraction rate using aeration rate. Simulation results run on a high complexity model of the process show that similar copper extraction rates can be obtained using either strategy. While better control efforts are obtained with MPC, ESC achieves similar results and shows potential for this intrinsically complex process, requiring little knowledge about the plant.